Fei SJ, Luo JY, Wang WH, Guo LX, Pan Q. Correlation between diabetic peripheral neuropathy and thyroid hormone sensitivity in elderly patients with type 2 diabetes mellitus. World J Diabetes 2025; 16(2): 98897 [DOI: 10.4239/wjd.v16.i2.98897]
Corresponding Author of This Article
Qi Pan, PhD, Chief Doctor, Department of Endocrinology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No. 1 Dahua Road, Dongcheng District, Beijing 100730, China. panqi621@126.com
Research Domain of This Article
Endocrinology & Metabolism
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Si-Jia Fei, Jing-Yi Luo, Wei-Hao Wang, Li-Xin Guo, Qi Pan, Department of Endocrinology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China
Author contributions: Pan Q, Guo LX and Fei SJ conceptualized and designed the research; Fei SJ, Luo JY and Wang WH screened patients and acquired clinical data; Fei SJ, Luo JY and Wang WH performed Data analysis; Fei SJ wrote the paper; All authors have reviewed and approved the final version of the manuscript for publication. Pan Q and Guo LX have both played essential and indispensable roles in the research design, data interpretation, and manuscript preparation as co-corresponding authors. Pan Q applied for and secured the funding for this research project. Pan Q conceptualized, designed, and supervised the entire project, conducted a literature review, and drafted the initial manuscript with a focus on the relationship between thyroid hormone sensitivity and diabetic peripheral neuropathy. Guo LX was instrumental in data re-analysis and interpretation, figure plotting, comprehensive literature review, and the preparation and submission of the current manuscript version, which focuses on FT3/FT4 as a potential predictor of peripheral neuropathy in elderly patients with type 2 diabetes. The collaboration between Pan Q and Guo LX is crucial for the publication of this manuscript.
Supported by the National Natural Science Foundation of China, No. 82270881 and No. 82200928; and National High-Level Hospital Clinical Research Funding, No. BJ-2023-124 and No. BJ-2023-130.
Institutional review board statement: This study received approval from the Research Committee of Beijing Hospital (No. 2024BJYYEC-KY094) and was conducted following the principles of the Declaration of Helsinki.
Informed consent statement: The requirement for written informed consent was waived.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Qi Pan, PhD, Chief Doctor, Department of Endocrinology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No. 1 Dahua Road, Dongcheng District, Beijing 100730, China. panqi621@126.com
Received: July 10, 2024 Revised: October 23, 2024 Accepted: November 26, 2024 Published online: February 15, 2025 Processing time: 174 Days and 1.4 Hours
Abstract
BACKGROUND
Diabetic peripheral neuropathy (DPN) is a common complication of type 2 diabetes mellitus (T2DM), significantly affecting patients’ quality of life and imposing a substantial economic burden. Recent studies have highlighted the role of thyroid hormones in diabetes complications, particularly in elderly patients with T2DM. However, the relationship between thyroid hormone sensitivity and DPN remains unclear.
AIM
To investigate the correlation between thyroid hormone sensitivity and DPN in elderly patients with T2DM.
METHODS
In a cohort of 256 elderly patients with T2DM, propensity score matching was used to balance age, sex, and diabetes duration. Clinical data were collected to calculate thyroid hormone sensitivity and analyze its correlation with DPN. A random forest model was used to evaluate the diagnostic value of free triiodothyronine/free thyroxine (FT3/FT4) for DPN.
RESULTS
Patients with DPN had a lower FT3/FT4 ratio [ (0.302 ± 0.053) vs (0.316 ± 0.049), P = 0.040]. Quartile stratification showed decreasing DPN prevalence with higher FT3/FT4 ratios. Spearman’s correlation analysis showed that a lower FT3/FT4 ratio was associated with higher glycated hemoglobin, fasting blood glucose, reduced nerve conduction velocity, and electrical skin conductance. Logistic regression indicated a positive relationship between the median FT3/FT4 ratio and bilateral foot electrochemical skin conductance [odds ratio (OR): 1.019; 95%CI: 1.005-1.034; P = 0.007] and sural nerve sensory amplitude (OR: 1.310; 95%CI: 1.008-1.703; P = 0.043). Receiver operating characteristic analysis using a random forest model showed that incorporating FT3/FT4 improved predictive performance for DPN, with an area under the curve of 0.74, sensitivity of 0.79, specificity of 0.64, and accuracy of 0.77.
CONCLUSION
In elderly patients with T2DM with euthyroidism, a lower FT3/FT4 ratio is correlated with increased DPN incidence, affecting both large and small nerve fibers. FT3/FT4 is an effective predictor of DPN.
Core Tip: In this study, we explore the relationship between thyroid hormone sensitivity and diabetic peripheral neuropathy (DPN) in elderly patients with type 2 diabetes mellitus (T2DM). Our findings indicate that a lower free triiodothyronine/free thyroxine (FT3/FT4) ratio is significantly associated with increased DPN incidence, affecting both large and small nerve fibers. The FT3/FT4 ratio serves as an effective predictor for DPN, enhancing diagnostic accuracy. These results highlight the importance of assessing thyroid hormone sensitivity in managing and predicting DPN in elderly patients with T2DM, offering new insights into the pathophysiological mechanisms underlying this complication.
Citation: Fei SJ, Luo JY, Wang WH, Guo LX, Pan Q. Correlation between diabetic peripheral neuropathy and thyroid hormone sensitivity in elderly patients with type 2 diabetes mellitus. World J Diabetes 2025; 16(2): 98897
Diabetic peripheral neuropathy (DPN) is a prevalent complication of type 2 diabetes mellitus (T2DM), affecting approximately 50% of patients with diabetes[1]. DPN is characterized by pain and sensory impairment in the limbs and can lead to falls, ulcers, and fractures. In severe cases, it may necessitate amputation, thereby significantly diminishing patients’ quality of life and imposing a notable economic burden[1-3].
Thyroid hormones play a crucial role in regulating metabolism, energy balance, and the development and function of the nervous system[4]. Recent studies have gradually uncovered the relationship between thyroid dysfunction and insulin resistance, while chronic complications of diabetes, specifically, thyroid dysfunction has been implicated in the development of DPN[5,6]. Research has found that the prevalence of clinical and subclinical hypothyroidism (SCH) among patients with DPN is 17.7%, with 52.8% of patients with SCH exhibiting severe DPN, significantly higher than the 28.3% observed in the control group. This suggests an independent association between SCH and the severity of DPN[6]. Other studies have found that low triiodothyronine (T3) syndrome is associated with a higher risk and severity of DPN in patients with T2DM[7]. Elderly individuals are at high risk for thyroid diseases, with studies reporting that 23.79% of elderly patients with T2DM have thyroid dysfunction[8]. Some studies indicate that age influences the upper limit of thyroid-stimulating hormone (TSH) levels[9,10], suggesting that adult diagnostic and treatment protocols for thyroid diseases may not be appropriate for elderly patients. This highlights the need to explore other indicators to better understand the association between thyroid function and DPN in elderly patients with T2DM.
Recent studies suggest that thyroid hormone sensitivity is a more profound indicator of thyroid function status and is associated with T2DM, obesity, metabolic syndrome, and nonalcoholic fatty liver disease[11,12]. Despite this, there remains a lack of clarity regarding how thyroid hormone sensitivity impacts the progression of DPN in elderly patients with T2DM. Therefore, in this study, we aimed to explore the relationship between DPN and thyroid hormone sensitivity in elderly patients with T2DM and euthyroidism.
MATERIALS AND METHODS
Patients
This was a cross-sectional study that included patients who were electively hospitalized for routine diabetes management in the Endocrinology Department of Beijing Hospital from January 2020 to March 2023.
The inclusion criteria were as follows: (1) Age ≥ 65 years; (2) Diagnosis of T2DM, with diagnostic criteria referring to the 2023 guidelines of the American Diabetes Association, which include typical symptoms of diabetes plus either random blood glucose levels, 2-hour glucose levels during an oral glucose tolerance test, FBG ≥ 7.0 mmol/L, or glycated hemoglobin ≥ 48 mmol/L (6.5%)[13]; and (3) Normal thyroid function.
The exclusion criteria included the following: (1) History of thyroid disease, thyroid surgery, or long-term medication for thyroid disease; (2) Other types of diabetes, including type 1 diabetes mellitus, gestational diabetes, specific types of diabetes, low T3 syndrome, or acute complications of diabetes; (3) Severe liver dysfunction (aspartate aminotransferase or alanine aminotransferase > 2.5 times the upper limit of normal), severe renal dysfunction (estimated glomerular filtration rate < 30 mL/minute/1.73 m2), or malignant tumors; (4) History of pituitary disease; and (5) Non-diabetic causes of peripheral neuropathy.
To ensure that the peripheral neuropathy observed in this study was specifically attributed to diabetes, we applied strict exclusion criteria, ruling out patients with conditions such as cervical or lumbar spine disease, vitamin B12 deficiency, alcohol abuse, or other neurological disorders. Participants were classified into two groups based on the presence of DPN: Those with DPN (n = 161) and those without DPN (NDPN group) (n = 95). The enrollment flowchart is presented in Figure 1. This study received approval from the Research Committee of Beijing Hospital (2024BJYYEC-KY094-01) and was conducted following the principles of the Declaration of Helsinki.
Figure 1 Flow diagram showing the selection of the study population.
DPN: Diabetic peripheral neuropathy; NDPN: Non diabetic peripheral neuropathy; PSM: Propensity score matching; T2DM: Type 2 diabetes mellitus.
Sample size calculation
The sample size for this study was calculated using G*Power software in the study design phase, and the calculation method was reviewed for ethical approval. We estimated the required sample size based on an assumed effect size (correlation coefficient, r = 0.3), a significance level (α = 0.05), and a statistical power of 80% (1 - β = 0.80). The sample size was calculated using a two-tailed test with the point biserial correlation model, suitable for analyzing a dichotomous and continuous variable. This indicated a need for at least 82 participants per group, with a balanced allocation of DPN and NDPN groups (1:1), totaling 164 participants. The actual sample size was larger, further increasing the study’s statistical power and reliability.
Data collection and laboratory measurements
For all participants, we recorded the general demographic and clinical information, including age (years), sex, duration of diabetes (years), height (m), and weight (kg), and calculated the body mass index (BMI) using the formula: BMI (kg/m²) = weight (kg)/[height (m)²]. We also documented each participant’s history of hypertension, smoking, and alcohol use. Biochemical parameters, including total cholesterol, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), albumin, uric acid, and fasting blood glucose (FBG), were quantitatively assessed using the HITACHI LABOSPECT 008AS automated electrochemiluminescence immunoassay platform. Thyroid function was evaluated by analyzing TSH, free T3 (FT3), and free thyroxine (FT4) levels using the Siemens ADVIA Centaur automated immunoassay system. In addition, glycated hemoglobin (HbA1c) levels were measured using the Premier Hb9210 High-Performance Liquid Chromatography system. The reference ranges for FT3, FT4, and TSH were established as 2.3-4.2 pg/mL, 0.89-1.76 ng/dL, and 0.35-5.5 mIU/mL, respectively.
Calculation of thyroid hormone sensitivity indices
The thyroid hormone sensitivity indices were differentiated into central and peripheral categories. Central thyroid hormone sensitivity was assessed using indices such as the TSH Index (TSHI), Thyroid Hormone Resistance Index (TT4RI), and Thyroid Feedback Quantile Index (TFQI). TFQI was calculated using the formula: TFQI = cdfFT4 (1 - cdfTSH), where cdfFT4 and cdfTSH represent the cumulative distribution functions of FT4 and TSH, respectively, within the study population. These CDF values help assess the relative position of FT4 and TSH levels among the participants. The TFQI values ranged from -1 to 1. Negative TFQI values signified increased pituitary sensitivity to thyroid hormones, indicating a more responsive central sensitivity, whereas positive values denoted reduced sensitivity[11]. Higher TSHI and TT4RI indicated diminished central thyroid hormone sensitivity. The formulas for these indices were as follows: TSHI = Ln [TSH (mlU/L)] + 0.1345 × FT4 (pmol/L)[14], and TT4RI = FT4 (pmol/L) × TSH (mIU/L)[11]. For peripheral thyroid hormone sensitivity, the ratio of FT3 to FT4 served as the primary indicator, with an elevated FT3/FT4 ratio suggesting enhanced peripheral activity. This assessment was based on the premise that FT3, which is the active form of thyroid hormones, plays a crucial role in peripheral thyroid activity[15,16].
Diagnosis of DPN
A comprehensive five-part screening was conducted to detect DPN. This included evaluation of ankle reflexes, vibration perception testing with a 128 Hz tuning fork, pressure perception testing with a 10 g monofilament, pinprick pain perception testing, and temperature sensitivity testing. Additionally, any experiences of pain symptoms and sensory abnormalities were thoroughly investigated. DPN was defined based on positive findings in two or more of the sensory symptoms, signs, or reflex abnormalities, along with changes in ankle reflexes consistent with distal symmetric polyneuropathy and nerve conduction abnormalities involving two or more nerves, including the median, peroneal, and sural nerves, thus confirming DPN[17]. DPN was treated as a binary outcome, with patients classified into DPN and NDPN groups based on the diagnostic criteria.
Nerve conduction studies
Electrochemical skin conductance (ESC) was measured on both hands and feet, and the nerve fiber conduction velocity, latency, and amplitude were assessed using electromyography. The results were determined by trained professionals to ensure consistency and reliability.
Statistical analysis
Data processing and analysis were conducted using SPSS version 23 (IBM SPSS, Chicago, IL, United States) and Python 3.11. Propensity score matching (PSM) analysis was conducted to adjust for imbalances in age, sex, and duration of diabetes. Matching was performed at a 1:2 ratio with a caliper width of 0.2[18,19]. The Kolmogorov-Smirnov test was first applied to assess the normality of the data. For data following a normal distribution, the metric was presented as the mean ± SD and compared between groups using the independent samples t-test; data not following a normal distribution are represented by the median (P25-P75) and were compared using the non-parametric Mann-Whitney U test. Categorical data are expressed as percentages (%) and were analyzed using the χ2 test. Missing values in the data were imputed using regression estimation. Spearman’s correlation analysis was used to assess the relationship between thyroid hormone sensitivity nerve conduction indices, and skin conductance levels. Furthermore, logistic regression models were applied to explore the associations between FT3/FT4 ratio stratification nerve conduction indices and skin conductance levels. A two-sided P value < 0.05 was considered statistically significant. Finally, the random forest model was applied to plot the receiver operating characteristic (ROC) curve to evaluate the effectiveness of FT3/FT4 in predicting DPN.
RESULTS
Comparison of general characteristics and biochemical indices of the study participants
Following the inclusion and exclusion criteria and after PSM, 161 patients with DPN (DPN group) and 95 patients without DPN (NDPN group) were enrolled in the study. Compared to the NDPN group, the DPN group had a lower FT3/FT4 ratio [(0.302 ± 0.053) vs (0.316 ± 0.049), P = 0.040], and lower HDL-C levels [1.03 (0.92-1.21) vs 1.19 (1.01-1.36), P = 0.001]. A comparison of baseline data between the two groups is presented in Table 1.
Table 1 Comparison of the general characteristics and biochemical indices between the two groups, n (%).
Correlation between FT3/FT4 stratification and DPN
The study population was divided into four groups based on the quartiles of the FT3/FT4 ratio (Supplementary Figure 1). The proportion of DPN in each group was compared. Results showed that as the FT3/FT4 ratio increased, the proportion of DPN decreased, with the percentages of DPN in the four groups being 70.8%, 65.6%, 58.5%, and 56.5%, respectively (P = 0.021). There was a significant difference in the proportion of DPN across the FT3/FT4 ratio quartiles, suggesting a potential correlation between the two.
Correlation between thyroid hormone sensitivity and metabolic indicators
Further analysis explored the relationship between thyroid hormone sensitivity indicators and metabolic markers (Supplementary Figure 2). The findings revealed a negative correlation between the FT3/FT4 ratio and both HbA1c (%) (r = -0.1944, P = 0.003) and FBG levels (r = -0.197, P = 0.002).
Correlation analysis between FT3/FT4 levels and neuro conductivity and skin conductance indicators
A correlation analysis was conducted between FT3/FT4 levels and neuro conductivity and skin conductance indicators (Table 2). The results indicated that FT3/FT4 levels were positively correlated with motor velocity in the median nerve (r = 0.156, P = 0.013), as well as with ESC in both feet (r = 0.177, P = 0.005) and hands (r = 0.154, P = 0.015).
Table 2 Correlation analysis between free triiodothyronine/free thyroxine levels and neuro conductivity and skin conductance indicators.
r
P value
Median nerve motor latency (millisecond)
-0.093
0.139
Median nerve motor amplitude (mV)
0.076
0.226
Median nerve motor velocity (m/second)
0.156
0.013
Common peroneal nerve motor latency (millisecond)
0.012
0.848
Common peroneal nerve motor amplitude (mV)
-0.027
0.670
Common peroneal nerve motor velocity (m/second)
0.027
0.667
Median nerve sensory latency (millisecond)
-0.103
0.101
Median nerve sensory amplitude (mV)
0.107
0.089
Median nerve sensory velocity (m/second)
0.098
0.117
Common peroneal nerve sensory latency (millisecond)
-0.028
0.662
Common peroneal nerve sensory amplitude (mV)
0.076
0.225
Common peroneal nerve sensory velocity (m/second)
0.040
0.526
F-min (millisecond)
-0.084
0.186
M-latency (millisecond)
-0.088
0.161
Two-legged ESC (microsecond)
0.177
0.005
Two-handed ESC (microsecond)
0.154
0.015
Correlation between FT3/FT4 stratification and neuro conductivity and skin conductance indicators
Participants were categorized into two groups based on the median FT3/FT4 ratio. Binary logistic regression analysis was used to compare the correlation between these groups and neuroconductivity and skin conductance indicators. Model 1 adjusted for variables that showed statistical differences in the correlation analysis: Median nerve motor velocity, ESC in both feet, and ESC in both hands. Model 2 was adjusted for median nerve motor latency, median nerve motor amplitude, median nerve motor velocity, peroneal nerve motor latency, peroneal nerve motor amplitude, peroneal nerve motor velocity, median nerve sensory amplitude, peroneal nerve sensory latency, peroneal nerve sensory amplitude, peroneal nerve sensory velocity, ESC in both feet and ESC in both hands. The results are presented in Table 3, indicating that an increase in the FT3/FT4 ratio was associated with an increase in ESC in both feet [odds ratio (OR): = 1.019; 95%CI: 1.005-1.034; P = 0.043].
Table 3 Association between free triiodothyronine/free thyroxine stratification and neuro conductivity, skin conductance indicators.
Odds ratio
95%CI
P value
Model 1
Two-legged ESC (microsecond)
1.017
1.004-1.031
0.013
Model 2
Two-legged ESC (microsecond)
1.019
1.005-1.034
0.007
Common peroneal nerve sensory amplitude (mV)
1.310
1.008-1.703
0.043
Evaluation of the predictive value of FT3/FT4 for DPN using ROC curve analysis
To evaluate the predictive value of FT3/FT4 for DPN, a random forest model was employed to generate ROC curves (Figure 2). Initially, a model was constructed using known risk factors for DPN[20] (including age, sex, duration of diabetes, hypertension, smoking, LDL-C, TG, HbA1c, FBG, and BMI) to generate the original ROC curve (labeled as “original”). Subsequently, FT3/FT4 was added as an additional feature, and a new ROC curve was generated (labeled as “FT3/FT4”). In the original model without FT3/FT4, the accuracy was 0.73, the area under the curve (AUC) was 0.68, the sensitivity was 0.53, and the specificity was 0.86. After including FT3/FT4, the model’s accuracy increased to 0.77, the AUC improved to 0.74, the sensitivity rose to 0.79, and the specificity decreased to 0.64. The AUC serves as a comprehensive evaluation index of sensitivity and specificity. The inclusion of FT3/FT4 resulted in the highest AUC and accuracy, indicating that FT3/FT4 is a valuable biomarker in assisting in the diagnosis of DPN and enhancing the performance of the diagnostic model.
Figure 2 Receiver operating characteristic curve of free triiodothyronine/free thyroxine for predicting diabetic peripheral neuropathy.
The receiver operating characteristic (ROC) curve plotted based on the random forest model evaluates the value of free triiodothyronine/free thyroxine (FT3/FT4) in predicting DPN. First, we used age, sex, duration of diabetes, hypertension, smoking, low-density lipoprotein cholesterol, triglycerides, hormglycated, fasting blood glucose, and body mass index to construct the model and generate the ROC curve (labeled as “original”). Then, we included FT3/FT4 as an additional feature in the model and generated a new ROC curve (labeled as “FT3/FT4”). ROC: Receiver operating characteristic; AUC: Area under the curve; FT3/FT4: Free triiodothyronine/free thyroxine ratio.
DISCUSSION
In this study, we thoroughly investigated the correlation between DPN and thyroid hormone sensitivity among elderly patients with T2DM who had normal thyroid function. By employing PSM to adjust for age, sex, and duration of diabetes, it was discovered that in elderly patients with T2DM, a decrease in the FT3/FT4 ratio, indicative of reduced peripheral sensitivity to thyroid hormones, significantly increased the incidence of DPN. The FT3/FT4 ratio was positively correlated with the motor velocity of the median nerve, ESC in both hands, and ESC in both feet. FT3/FT4 is an effective predictor of DPN. Additionally, the FT3/FT4 ratio was found to negatively correlate with glycemic metabolic indicators. Importantly, as shown in Table 1, the duration of diabetes was well-balanced between the DPN and NDPN groups (P = 0.820), indicating that diabetes duration did not act as a confounding factor in our analysis.
The relationship between thyroid dysfunction and DPN is a topic worth exploring. A study by Zhao et al[5], which included 605 patients with T2DM, found that TSH was an independent risk factor for DPN (OR = 1.365, P < 0.01). More recently, a study involving 580 patients with T2DM explored whether thyroid function indicators affect DPN in patients with T2DM with normal thyroid function. They discovered that FT4 levels were inversely related to the prevalence of DPN in patients with normal thyroid function. Specifically, when FT4 levels were below 18.3 pmol/L, the incidence of DPN significantly increased, whereas no significant correlation was observed between TSH, FT3, thyroxine (T4), and T3 levels and DPN[21]. However, another study reached different conclusions, suggesting that FT4 levels were positively correlated with the prevalence of DPN, whereas FT3 levels were inversely related[22]. These findings indicate that using TSH or thyroid hormones alone is insufficient to explain the complex relationship between thyroid hormones and DPN. Therefore, we explored the correlation between thyroid hormone sensitivity, a more in-depth indicator of thyroid function status, and DPN. Our study found that thyroid hormone sensitivity was related to the occurrence of DPN in elderly patients with T2DM and normal thyroid function, suggesting that thyroid hormones plays a role not only in the regulation of systemic metabolism but may also directly or indirectly affect the health of the nervous system.
To ensure that the peripheral neuropathy observed in this study was primarily due to diabetes and not age-related factors, we applied strict inclusion and exclusion criteria. We excluded patients with non-diabetic causes of neuropathy, such as spine disease, vitamin B12 deficiency, or alcohol abuse. All patients had confirmed DPN based on clinical symptoms and nerve conduction studies. Additionally, we used PSM to adjust for age, and as shown in Table 1, there was no significant age difference between the DPN and NDPN groups (P = 0.976). These steps ensured that the observed associations between thyroid hormone sensitivity and neuropathy were specific to diabetes.
The underlying mechanisms linked to FT3 with DPN remain unclear. Degeneration of peripheral vascular endothelial cells is considered one of the characteristic changes in DPN[23,24], in which the associated reduction in nitric oxide (NO) due to endothelial dysfunction plays a key role[25]. Studies have shown that T3 mediates NO production in endothelial cells, reducing DPN by protecting the microvascular endothelium[26]. Furthermore, the production of 3,5-diiodothyronine through the deiodination pathway of T3 may help to reverse the progression of DPN by regulating the expression of Sirtuin 1 protein[27]. The study by Bessede et al[28] demonstrated that T3 can promote the regeneration of the cavernous nerve and sciatic nerve, further supporting the role of T3 in nerve regeneration and repair. These findings are consistent with the negative correlation between FT3 levels, abnormalities in nerve conduction, and the risk of DPN. Specifically, T3 has been shown to have a direct or indirect impact on vascular endothelial function, assisting in the improvement of endothelial function by relaxing vascular smooth muscles. Meanwhile, low levels of FT3 may promote the development of DPN by affecting endothelial function[29]. Further research indicates that T3 can reduce the activity of phosphatidylinositol 3-kinase and increase the expression of transforming growth factor-β1[30], potentially accelerating the progression of DPN[31]. This suggests a close correlation between FT3 levels and the development of DPN.
The conversion of FT4 into the more active FT3 exerts potent biological effects on target organs and tissues, primarily catalyzed by type II deiodinase (DIO2), and the FT3/FT4 ratio reflects the activity of DIO2[22]. Activation of DIO2 can reduce oxidative stress and diminish inflammatory responses. However, in patients with T2DM, reduced activity of DIO2 leads to decreased production of FT3, increased oxidative stress, and inflammation, which in turn promotes the development of DPN[32]. Bapputty et al[33] found that DIO2 expression was significantly reduced in the retinas of diabetic mice, and a high-glucose environment further impaired DIO2 activity, suggesting that downregulation of DIO2 may play a role in diabetes-related complications. Although direct evidence linking DIO2 to DPN is lacking, it is plausible that reduced DIO2 activity may also contribute to the progression of DPN. The relationship between thyroid hormone levels and the occurrence of DPN is complex. For the early diagnosis and prevention of DPN, it is recommended that patients with normal thyroid function and diabetes undergo regular screening and thyroid hormone testing.
In the assessment of thyroid function, FT3 and FT4 are crucial indicators representing the levels of active and stored thyroid hormones in the body, respectively. The FT3/FT4 ratio is used to assess the efficiency of conversion from T4 to T3, indirectly reflecting peripheral sensitivity to thyroid hormones. T3 is one of the most important stimulatory factors in peripheral nerve regeneration. Research has shown that local application of T3 significantly increases the number of regenerating axons and myelination following the transection of the sciatic nerve in rats[34]. Furthermore, local and single administration of T3 within biodegradable nerve conduits can notably improve the regeneration of severed peripheral nerves and accelerate functional recovery[35]. However, there remains a lack of research exploring the correlation between thyroid hormone sensitivity and the function of large and small nerve fibers. This study pioneers the proposition that a decrease in peripheral sensitivity to thyroid hormones may simultaneously impair both large and small nerve fibers. Given the absence of a unified standard for assessing peripheral sensitivity to thyroid hormones, further validation of this conclusion requires multicenter studies with large sample sizes.
Using a random forest model to plot the ROC curve, we found that the FT3/FT4 ratio is a powerful indicator in predicting DPN. The random forest model, as a machine learning method capable of handling complex data relationships, combined with the ROC curve, provides a reliable means of evaluating diagnostic performance. In this study, the inclusion of the FT3/FT4 ratio led to an increase in the model’s AUC value and classification accuracy, indicating a strong correlation between FT3/FT4 and the risk assessment of DPN. This finding may be related to the critical role of thyroid hormones in maintaining nerve health. In clinical practice, prioritizing sensitivity in DPN screening is crucial for early detection and timely intervention. Although the specificity decreased slightly, this trade-off is acceptable to minimize missed diagnoses, which can lead to severe complications.
This study also discovered a correlation between thyroid hormone sensitivity and glycemic metabolism, with the FT3/FT4 ratio found to be negatively associated with HbA1c and FBG levels. A decrease in peripheral sensitivity to thyroid hormones coincided with higher blood glucose levels. Poor long-term glycemic control is a risk factor for DPN[36]. Numerous studies have indicated that thyroid hormones play a significant role in glucose metabolism, with no shortage of research on the impact of thyroid hormone levels on glycemic metabolism. Elevated levels of FT3 are associated with improved insulin resistance, decreased gluconeogenesis, and reduced hyperglucagonemia[37]. Gu et al[38] found that low levels of free thyroid hormones within the normal range are significantly associated with high blood glucose levels and severe insulin resistance. Falkowski et al[39] conducted a study on patients with type 1 diabetes mellitus and normal thyroid function and reported that lower levels of FT3 were linked to a higher rate of neurovascular complications and poorer diabetes metabolic control. These findings suggest that thyroid hormone sensitivity indirectly promotes the occurrence of DPN by affecting glycemic metabolism.
This study has several limitations. First, as an observational study, it could not establish causality. Second, the methods for assessing thyroid hormone sensitivity were not standardized, and criteria may vary across studies. Third, the small sample size limited the robustness of our conclusions, and larger studies are needed. Additionally, restricting the study to patients aged 65 and older may limit generalizability to younger populations. Furthermore, the sensitivity and specificity of neuroconductivity and skin conductance indicators may have affected the diagnostic accuracy, potentially leading to underdiagnosis or overdiagnosis of DPN. Lastly, we did not analyze the effects of medications that could influence thyroid function or DPN, which future studies should consider to strengthen the findings.
CONCLUSION
In summary, among elderly patients with T2DM and normal thyroid function, a decrease in peripheral thyroid hormone sensitivity was associated with an increased incidence of DPN. FT3/FT4 is an effective predictor of DPN. In addition, a decrease in peripheral thyroid hormone sensitivity may affect both large and small nerve fiber pathology. This discovery provides new insights into the complex pathophysiological mechanisms underlying DPN.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Endocrinology and metabolism
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade A, Grade B, Grade B, Grade B, Grade C, Grade D
Novelty: Grade A, Grade B, Grade B, Grade B, Grade B
Creativity or Innovation: Grade B, Grade B, Grade B, Grade B, Grade C
Scientific Significance: Grade A, Grade B, Grade B, Grade B, Grade C
P-Reviewer: Anoop L; Byeon H; Cai L; Jamaluddin J S-Editor: Li L L-Editor: A P-Editor: Yu HG
Pop-Busui R, Ang L, Boulton AJM, Feldman EL, Marcus RL, Mizokami-Stout K, Singleton JR, Ziegler D.
Diagnosis and Treatment of Painful Diabetic Peripheral Neuropathy. Arlington (VA): American Diabetes Association, 2022.
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